{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d462dbf4",
   "metadata": {},
   "source": [
    "Copyright (c) MONAI Consortium  \n",
    "Licensed under the Apache License, Version 2.0 (the \"License\");  \n",
    "you may not use this file except in compliance with the License.  \n",
    "You may obtain a copy of the License at  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0  \n",
    "Unless required by applicable law or agreed to in writing, software  \n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,  \n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.  \n",
    "See the License for the specific language governing permissions and  \n",
    "limitations under the License.\n",
    "\n",
    "# Denoising Diffusion Probabilistic Models with MedNIST Dataset\n",
    "\n",
    "This tutorial compares the different schedulers available for sampling from a trained model with a reduced number of timesteps. The schedulers we will compare are:\n",
    "\n",
    "[1] - DDPM - Ho et al. \"Denoising Diffusion Probabilistic Models\" https://arxiv.org/abs/2006.11239\n",
    "\n",
    "[2] - DDIM - Song et al. \"Denoising Diffusion Implicit Models\" https://arxiv.org/abs/2010.02502\n",
    "\n",
    "[3] - PNDM - Liu et al. \"Pseudo Numerical Methods for Diffusion Models on Manifolds\" https://arxiv.org/abs/2202.09778\n",
    "\n",
    "\n",
    "\n",
    "## Setup environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "57c074c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python -c \"import monai\" || pip install -q \"monai-weekly[tqdm]\"\n",
    "!python -c \"import matplotlib\" || pip install -q matplotlib\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c45380e",
   "metadata": {},
   "source": [
    "## Setup imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cf51122f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MONAI version: 1.4.0rc6\n",
      "Numpy version: 1.26.4\n",
      "Pytorch version: 2.3.1+cu121\n",
      "MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False\n",
      "MONAI rev id: 6a0e1b043ba2890e1463fa49df76f66e56a68b08\n",
      "MONAI __file__: /home/<username>/miniconda3/envs/monai/lib/python3.11/site-packages/monai/__init__.py\n",
      "\n",
      "Optional dependencies:\n",
      "Pytorch Ignite version: 0.4.11\n",
      "ITK version: 5.4.0\n",
      "Nibabel version: 5.2.1\n",
      "scikit-image version: 0.23.2\n",
      "scipy version: 1.13.1\n",
      "Pillow version: 10.3.0\n",
      "Tensorboard version: 2.17.0\n",
      "gdown version: 5.2.0\n",
      "TorchVision version: 0.18.1+cu121\n",
      "tqdm version: 4.66.4\n",
      "lmdb version: 1.4.1\n",
      "psutil version: 5.9.0\n",
      "pandas version: 2.2.2\n",
      "einops version: 0.8.0\n",
      "transformers version: NOT INSTALLED or UNKNOWN VERSION.\n",
      "mlflow version: 2.14.0\n",
      "pynrrd version: 1.0.0\n",
      "clearml version: 1.16.2rc0\n",
      "\n",
      "For details about installing the optional dependencies, please visit:\n",
      "    https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import shutil\n",
    "import tempfile\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "from tqdm import tqdm\n",
    "from monai import transforms\n",
    "from monai.apps import MedNISTDataset\n",
    "from monai.config import print_config\n",
    "from monai.data import CacheDataset, DataLoader\n",
    "from monai.utils import first, set_determinism\n",
    "from monai.inferers import DiffusionInferer\n",
    "from monai.networks.nets import DiffusionModelUNet\n",
    "from monai.networks.schedulers import DDIMScheduler, DDPMScheduler, PNDMScheduler\n",
    "\n",
    "print_config()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d252fb96",
   "metadata": {},
   "source": [
    "## Setup data directory\n",
    "\n",
    "You can specify a directory with the MONAI_DATA_DIRECTORY environment variable.\n",
    "\n",
    "This allows you to save results and reuse downloads.\n",
    "\n",
    "If not specified a temporary directory will be used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2dddeec3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/tmpm4jzl5xr\n"
     ]
    }
   ],
   "source": [
    "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
    "root_dir = tempfile.mkdtemp() if directory is None else directory\n",
    "print(root_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac758b96",
   "metadata": {},
   "source": [
    "## Set deterministic training for reproducibility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "12f95a15",
   "metadata": {},
   "outputs": [],
   "source": [
    "set_determinism(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "223684c0",
   "metadata": {},
   "source": [
    "## Setup MedNIST Dataset and training and validation dataloaders\n",
    "In this tutorial, we will train our models on the MedNIST dataset available on MONAI\n",
    "(https://docs.monai.io/en/stable/apps.html#monai.apps.MedNISTDataset). In order to train faster, we will select just\n",
    "one of the available classes (\"Hand\"), resulting in a training set with 7999 2D images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0b9020fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = MedNISTDataset(root_dir=root_dir, section=\"training\", download=True, seed=0)\n",
    "train_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"Hand\"]\n",
    "batch_size = 64\n",
    "num_workers = 4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce22143f-4438-4af5-b9e9-2ad70fa1f17e",
   "metadata": {},
   "source": [
    "Here we use transforms to augment the training dataset:\n",
    "\n",
    "1. `LoadImaged` loads the hands images from files.\n",
    "1. `EnsureChannelFirstd` ensures the original data to construct \"channel first\" shape.\n",
    "1. `ScaleIntensityRanged` extracts intensity range [0, 255] and scales to [0, 1].\n",
    "1. `RandAffined` efficiently performs rotate, scale, shear, translate, etc. together based on PyTorch affine transform."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "32cc4e62",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading dataset: 100%|██████████| 7999/7999 [00:05<00:00, 1354.84it/s]\n"
     ]
    }
   ],
   "source": [
    "train_transforms = transforms.Compose(\n",
    "    [\n",
    "        transforms.LoadImaged(keys=[\"image\"]),\n",
    "        transforms.EnsureChannelFirstd(keys=[\"image\"]),\n",
    "        transforms.ScaleIntensityRanged(keys=[\"image\"], a_min=0.0, a_max=255.0, b_min=0.0, b_max=1.0, clip=True),\n",
    "        transforms.RandAffined(\n",
    "            keys=[\"image\"],\n",
    "            rotate_range=[(-np.pi / 36, np.pi / 36), (-np.pi / 36, np.pi / 36)],\n",
    "            translate_range=[(-1, 1), (-1, 1)],\n",
    "            scale_range=[(-0.05, 0.05), (-0.05, 0.05)],\n",
    "            spatial_size=[64, 64],\n",
    "            padding_mode=\"zeros\",\n",
    "            prob=0.5,\n",
    "        ),\n",
    "    ]\n",
    ")\n",
    "train_ds = CacheDataset(data=train_datalist, transform=train_transforms)\n",
    "train_loader = DataLoader(\n",
    "    train_ds, batch_size=batch_size, shuffle=True, num_workers=num_workers, persistent_workers=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c7b75be0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2024-09-02 18:24:30,579 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
      "2024-09-02 18:24:30,580 - INFO - File exists: /tmp/tmpm4jzl5xr/MedNIST.tar.gz, skipped downloading.\n",
      "2024-09-02 18:24:30,581 - INFO - Non-empty folder exists in /tmp/tmpm4jzl5xr/MedNIST, skipped extracting.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading dataset: 100%|██████████| 5895/5895 [00:02<00:00, 2488.46it/s]\n",
      "Loading dataset: 100%|██████████| 1005/1005 [00:00<00:00, 1390.42it/s]\n"
     ]
    }
   ],
   "source": [
    "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n",
    "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"Hand\"]\n",
    "val_transforms = transforms.Compose(\n",
    "    [\n",
    "        transforms.LoadImaged(keys=[\"image\"]),\n",
    "        transforms.EnsureChannelFirstd(keys=[\"image\"]),\n",
    "        transforms.ScaleIntensityRanged(keys=[\"image\"], a_min=0.0, a_max=255.0, b_min=0.0, b_max=1.0, clip=True),\n",
    "    ]\n",
    ")\n",
    "val_ds = CacheDataset(data=val_datalist, transform=val_transforms)\n",
    "val_loader = DataLoader(val_ds, batch_size=batch_size, shuffle=False, num_workers=num_workers, persistent_workers=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ab0e5cb",
   "metadata": {},
   "source": [
    "### Visualisation of the training images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b7b5a662",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "batch shape: torch.Size([128, 1, 64, 64])\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "check_data = first(train_loader)\n",
    "print(f\"batch shape: {check_data['image'].shape}\")\n",
    "image_visualisation = torch.cat(\n",
    "    [check_data[\"image\"][0, 0], check_data[\"image\"][1, 0], check_data[\"image\"][2, 0], check_data[\"image\"][3, 0]], dim=1\n",
    ")\n",
    "plt.figure(\"training images\", (12, 6))\n",
    "plt.imshow(image_visualisation, vmin=0, vmax=1, cmap=\"gray\")\n",
    "plt.axis(\"off\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6baa627b",
   "metadata": {},
   "source": [
    "### Define network and optimizer\n",
    "At this step, we instantiate the MONAI components to create a DDPM, a 2D unet with attention mechanisms\n",
    "in the 2nd and 4th levels, each with 1 attention head."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "17b0b16a",
   "metadata": {},
   "outputs": [],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "\n",
    "model = DiffusionModelUNet(\n",
    "    spatial_dims=2,\n",
    "    in_channels=1,\n",
    "    out_channels=1,\n",
    "    channels=(64, 128, 128),\n",
    "    attention_levels=(False, True, True),\n",
    "    num_res_blocks=1,\n",
    "    num_head_channels=128,\n",
    ")\n",
    "model.to(device)\n",
    "\n",
    "optimizer = torch.optim.Adam(model.parameters(), 2.5e-5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9345f57-b65a-4fae-9ffe-ad39db91f762",
   "metadata": {},
   "source": [
    "### Define schedulers\n",
    "\n",
    "We use a DDPM scheduler with 1000 steps for training. For sampling, we will compare the DDPM, DDIM, and PNDM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0fe646cd-1696-463c-8be0-20ab9c05d744",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_train_timesteps = 1000\n",
    "ddpm_scheduler = DDPMScheduler(num_train_timesteps=num_train_timesteps)\n",
    "ddim_scheduler = DDIMScheduler(num_train_timesteps=num_train_timesteps)\n",
    "pndm_scheduler = PNDMScheduler(num_train_timesteps=num_train_timesteps, skip_prk_steps=True)\n",
    "\n",
    "# the range of sampling steps we want to use when testing the DDIM and PNDM schedulers\n",
    "sampling_steps = [1000, 500, 200, 50]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48797080",
   "metadata": {},
   "source": [
    "### Define inferer for sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "25014ea6-dfb6-4cd3-93fa-4351197d6fa5",
   "metadata": {},
   "outputs": [],
   "source": [
    "inferer = DiffusionInferer(scheduler=ddpm_scheduler)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9857d42f",
   "metadata": {},
   "source": [
    "### Model training\n",
    "Here, we are training our model for 100 epochs (training time: ~40 minutes). It is necessary to train for a bit longer than other tutorials because the DDIM and PNDM schedules seem to require a model trained longer before they start producing good samples, when compared to DDPM.\n",
    "\n",
    "If you would like to skip the training and use a pre-trained model instead, set `use_pretrained=True`. This model was trained using the code in `tutorials/generative/distributed_training/ddpm_training_ddp.py`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "49a16601",
   "metadata": {
    "lines_to_next_cell": 0
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 0: 100%|██████████| 63/63 [00:21<00:00,  2.89it/s, loss=0.741]\n",
      "Epoch 1: 100%|██████████| 63/63 [00:21<00:00,  2.95it/s, loss=0.59] \n",
      "Epoch 2: 100%|██████████| 63/63 [00:21<00:00,  2.96it/s, loss=0.421]\n",
      "Epoch 3: 100%|██████████| 63/63 [00:21<00:00,  2.96it/s, loss=0.256]\n",
      "Epoch 4: 100%|██████████| 63/63 [00:21<00:00,  2.96it/s, loss=0.149]\n",
      "Epoch 5: 100%|██████████| 63/63 [00:21<00:00,  2.88it/s, loss=0.0957]\n",
      "Epoch 6: 100%|██████████| 63/63 [00:21<00:00,  2.94it/s, loss=0.0746]\n",
      "Epoch 7: 100%|██████████| 63/63 [00:21<00:00,  2.95it/s, loss=0.0651]\n",
      "Epoch 8: 100%|██████████| 63/63 [00:21<00:00,  2.94it/s, loss=0.0606]\n",
      "Epoch 9: 100%|██████████| 63/63 [00:21<00:00,  2.94it/s, loss=0.0596]\n",
      "...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 90: 100%|██████████| 63/63 [00:21<00:00,  2.92it/s, loss=0.0436]\n",
      "Epoch 91: 100%|██████████| 63/63 [00:21<00:00,  2.95it/s, loss=0.0446]\n",
      "Epoch 92: 100%|██████████| 63/63 [00:21<00:00,  2.95it/s, loss=0.0431]\n",
      "Epoch 93: 100%|██████████| 63/63 [00:21<00:00,  2.94it/s, loss=0.0439]\n",
      "Epoch 94: 100%|██████████| 63/63 [00:21<00:00,  2.96it/s, loss=0.0442]\n",
      "Epoch 95: 100%|██████████| 63/63 [00:21<00:00,  2.96it/s, loss=0.0443]\n",
      "Epoch 96: 100%|██████████| 63/63 [00:21<00:00,  2.94it/s, loss=0.0426]\n",
      "Epoch 97: 100%|██████████| 63/63 [00:21<00:00,  2.94it/s, loss=0.0435]\n",
      "Epoch 98: 100%|██████████| 63/63 [00:21<00:00,  2.95it/s, loss=0.0427]\n",
      "Epoch 99: 100%|██████████| 63/63 [00:21<00:00,  2.95it/s, loss=0.0443]\n",
      "Epoch 99 - Validation set:  13%|█▎        | 8/63 [00:00<00:06,  8.45it/s, val_loss=0.0468]\n",
      "100%|██████████| 1000/1000 [00:09<00:00, 101.98it/s]\n",
      "100%|██████████| 1000/1000 [00:09<00:00, 103.98it/s]\n",
      "100%|██████████| 500/500 [00:04<00:00, 105.15it/s]\n",
      "100%|██████████| 200/200 [00:01<00:00, 102.81it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 103.02it/s]\n",
      "100%|██████████| 1000/1000 [00:09<00:00, 103.27it/s]\n",
      "100%|██████████| 500/500 [00:04<00:00, 103.60it/s]\n",
      "100%|██████████| 200/200 [00:01<00:00, 103.34it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 103.02it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x400 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "use_pretrained = False\n",
    "\n",
    "if use_pretrained:\n",
    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models:v0.2\", model=\"ddpm_2d\", verbose=True).to(device)\n",
    "else:\n",
    "    max_epochs = 100\n",
    "    val_interval = 10\n",
    "    epoch_loss_list = []\n",
    "    val_epoch_loss_list = []\n",
    "    for epoch in range(max_epochs):\n",
    "        model.train()\n",
    "        epoch_loss = 0\n",
    "        progress_bar = tqdm(enumerate(train_loader), total=len(train_loader))\n",
    "        progress_bar.set_description(f\"Epoch {epoch}\")\n",
    "        for step, batch in progress_bar:\n",
    "            images = batch[\"image\"].to(device)\n",
    "            optimizer.zero_grad(set_to_none=True)\n",
    "\n",
    "            # Randomly select the timesteps to be used for the minibacth\n",
    "            timesteps = torch.randint(0, num_train_timesteps, (images.shape[0],), device=device).long()\n",
    "\n",
    "            # Add noise to the minibatch images with intensity defined by the scheduler and timesteps\n",
    "            noise = torch.randn_like(images).to(device)\n",
    "            noisy_image = ddpm_scheduler.add_noise(original_samples=images, noise=noise, timesteps=timesteps)\n",
    "\n",
    "            # In this example, we are parametrising our DDPM to learn the added noise (epsilon).\n",
    "            # For this reason, we are using our network to predict the added noise and then using L1 loss to predict\n",
    "            # its performance.\n",
    "            noise_pred = model(x=noisy_image, timesteps=timesteps)\n",
    "            loss = F.l1_loss(noise_pred.float(), noise.float())\n",
    "\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "            epoch_loss += loss.item()\n",
    "\n",
    "            progress_bar.set_postfix({\"loss\": epoch_loss / (step + 1)})\n",
    "        epoch_loss_list.append(epoch_loss / (step + 1))\n",
    "\n",
    "        if (epoch + 1) % val_interval == 0:\n",
    "            model.eval()\n",
    "            val_epoch_loss = 0\n",
    "            progress_bar = tqdm(enumerate(val_loader), total=len(train_loader))\n",
    "            progress_bar.set_description(f\"Epoch {epoch} - Validation set\")\n",
    "            for step, batch in progress_bar:\n",
    "                images = batch[\"image\"].to(device)\n",
    "                timesteps = torch.randint(0, num_train_timesteps, (images.shape[0],), device=device).long()\n",
    "                noise = torch.randn_like(images).to(device)\n",
    "                with torch.no_grad():\n",
    "                    noisy_image = ddpm_scheduler.add_noise(original_samples=images, noise=noise, timesteps=timesteps)\n",
    "                    noise_pred = model(x=noisy_image, timesteps=timesteps)\n",
    "                    val_loss = F.l1_loss(noise_pred.float(), noise.float())\n",
    "\n",
    "                val_epoch_loss += val_loss.item()\n",
    "                progress_bar.set_postfix({\"val_loss\": val_epoch_loss / (step + 1)})\n",
    "            val_epoch_loss_list.append(val_epoch_loss / (step + 1))\n",
    "\n",
    "            # Sampling image during training\n",
    "            noise = torch.randn((1, 1, 64, 64))\n",
    "            noise = noise.to(device)\n",
    "            image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=ddpm_scheduler)\n",
    "            plt.figure(figsize=(8, 4))\n",
    "            plt.subplot(3, len(sampling_steps), 1)\n",
    "            plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
    "            plt.tick_params(top=False, bottom=False, left=False, right=False, labelleft=False, labelbottom=False)\n",
    "            plt.ylabel(\"DDPM\")\n",
    "            plt.title(\"1000 steps\")\n",
    "            # DDIM\n",
    "            for idx, reduced_sampling_steps in enumerate(sampling_steps):\n",
    "                ddim_scheduler.set_timesteps(reduced_sampling_steps)\n",
    "                image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=ddim_scheduler)\n",
    "                plt.subplot(3, len(sampling_steps), len(sampling_steps) + idx + 1)\n",
    "                plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
    "                plt.ylabel(\"DDIM\")\n",
    "                if idx == 0:\n",
    "                    plt.tick_params(\n",
    "                        top=False, bottom=False, left=False, right=False, labelleft=False, labelbottom=False\n",
    "                    )\n",
    "                else:\n",
    "                    plt.axis(\"off\")\n",
    "                plt.title(f\"{reduced_sampling_steps} steps\")\n",
    "            # PNDM\n",
    "            for idx, reduced_sampling_steps in enumerate(sampling_steps):\n",
    "                pndm_scheduler.set_timesteps(reduced_sampling_steps)\n",
    "                image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=pndm_scheduler)\n",
    "                plt.subplot(3, len(sampling_steps), len(sampling_steps) * 2 + idx + 1)\n",
    "                plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
    "                plt.ylabel(\"PNDM\")\n",
    "                if idx == 0:\n",
    "                    plt.tick_params(\n",
    "                        top=False, bottom=False, left=False, right=False, labelleft=False, labelbottom=False\n",
    "                    )\n",
    "                else:\n",
    "                    plt.axis(\"off\")\n",
    "                plt.title(f\"{reduced_sampling_steps} steps\")\n",
    "            plt.suptitle(f\"Epoch {epoch+1}\")\n",
    "            plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1e55da9",
   "metadata": {},
   "source": [
    "### Learning curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "af10be41",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if not use_pretrained:\n",
    "    plt.title(\"Learning Curves\", fontsize=20)\n",
    "    plt.plot(np.linspace(1, max_epochs, max_epochs), epoch_loss_list, color=\"C0\", linewidth=2.0, label=\"Train\")\n",
    "    plt.plot(\n",
    "        np.linspace(val_interval, max_epochs, int(max_epochs / val_interval)),\n",
    "        val_epoch_loss_list,\n",
    "        color=\"C1\",\n",
    "        linewidth=2.0,\n",
    "        label=\"Validation\",\n",
    "    )\n",
    "    plt.yticks(fontsize=12)\n",
    "    plt.xticks(fontsize=12)\n",
    "    plt.xlabel(\"Epochs\", fontsize=16)\n",
    "    plt.ylabel(\"Loss\", fontsize=16)\n",
    "    plt.legend(prop={\"size\": 14})\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1e10277-c0d8-43a4-8e5b-8ba58af7acfe",
   "metadata": {},
   "source": [
    "### Compare samples from trained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "518910a7-ec0b-4885-811b-2e47641195ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:09<00:00, 100.68it/s]\n",
      "100%|██████████| 1000/1000 [00:09<00:00, 102.23it/s]\n",
      "100%|██████████| 500/500 [00:04<00:00, 102.93it/s]\n",
      "100%|██████████| 200/200 [00:01<00:00, 103.34it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 103.18it/s]\n",
      "100%|██████████| 1000/1000 [00:09<00:00, 103.34it/s]\n",
      "100%|██████████| 500/500 [00:04<00:00, 103.16it/s]\n",
      "100%|██████████| 200/200 [00:01<00:00, 103.60it/s]\n",
      "100%|██████████| 50/50 [00:00<00:00, 104.01it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x400 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "noise = torch.randn((1, 1, 64, 64))\n",
    "noise = noise.to(device)\n",
    "image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=ddpm_scheduler)\n",
    "plt.figure(figsize=(8, 4))\n",
    "plt.subplot(3, len(sampling_steps), 1)\n",
    "plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
    "plt.tick_params(top=False, bottom=False, left=False, right=False, labelleft=False, labelbottom=False)\n",
    "plt.ylabel(\"DDPM\")\n",
    "plt.title(\"1000 steps\")\n",
    "# DDIM\n",
    "for idx, reduced_sampling_steps in enumerate(sampling_steps):\n",
    "    ddim_scheduler.set_timesteps(reduced_sampling_steps)\n",
    "    image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=ddim_scheduler)\n",
    "    plt.subplot(3, len(sampling_steps), len(sampling_steps) + idx + 1)\n",
    "    plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
    "    plt.ylabel(\"DDIM\")\n",
    "    if idx == 0:\n",
    "        plt.tick_params(top=False, bottom=False, left=False, right=False, labelleft=False, labelbottom=False)\n",
    "    else:\n",
    "        plt.axis(\"off\")\n",
    "    plt.title(f\"{reduced_sampling_steps} steps\")\n",
    "# PNDM\n",
    "for idx, reduced_sampling_steps in enumerate(sampling_steps):\n",
    "    pndm_scheduler.set_timesteps(reduced_sampling_steps)\n",
    "    image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=pndm_scheduler)\n",
    "    plt.subplot(3, len(sampling_steps), len(sampling_steps) * 2 + idx + 1)\n",
    "    plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
    "    plt.ylabel(\"PNDM\")\n",
    "    if idx == 0:\n",
    "        plt.tick_params(top=False, bottom=False, left=False, right=False, labelleft=False, labelbottom=False)\n",
    "    else:\n",
    "        plt.axis(\"off\")\n",
    "    plt.title(f\"{reduced_sampling_steps} steps\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "063331ff-f4d1-4780-a103-d1b1829af35c",
   "metadata": {},
   "source": [
    "### Cleanup data directory\n",
    "Remove directory if a temporary was used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "78058049-f92b-42b8-96f2-1eafca11a384",
   "metadata": {},
   "outputs": [],
   "source": [
    "if directory is None:\n",
    "    shutil.rmtree(root_dir)"
   ]
  }
 ],
 "metadata": {
  "jupytext": {
   "formats": "ipynb,py:percent"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
